Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Mathematical model--tell us the future!

Pentti Huovinen1

  • 1Antimicrobial Research Laboratory, Department of Bacterial and Inflammatory Diseases, National Public Health Institute, Finland. pentti.huovinen@ktl.fi

The Journal of Antimicrobial Chemotherapy
|June 24, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Nalidixic acid-a good marker of fluoroquinolone resistance mechanisms in <i>Escherichia coli</i>.

Microbiology spectrum·2025
Same author

High-throughput DNA extraction strategy for fecal microbiome studies.

Microbiology spectrum·2024
Same author

Association of Long-Term Habitual Dietary Fiber Intake since Infancy with Gut Microbiota Composition in Young Adulthood.

The Journal of nutrition·2024
Same author

An Infancy-Onset 20-Year Dietary Counselling Intervention and Gut Microbiota Composition in Adulthood.

Nutrients·2022
Same author

A Tribute to George A. Jacoby.

Antimicrobial agents and chemotherapy·2022
Same author

Time series analysis of the incidence of acute upper respiratory tract infections, COVID-19 and the use of antibiotics in Finland during the COVID-19 epidemic: a cohort study of 833 444 patients.

BMJ open·2022
Same journal

Favipiravir tissue distribution and inhibitory quotients in preclinical models: towards a pipeline for evidence-based antiviral repurposing.

The Journal of antimicrobial chemotherapy·2026
Same journal

A review of the randomized clinical trial results from the Staphylococcus aureus network adaptive platform (SNAP) meticillin-susceptible (MSSA) and penicillin-susceptible (PSSA) domains and CloCeBa.

The Journal of antimicrobial chemotherapy·2026
Same journal

Incidence and factors associated with subtherapeutic cefazolin levels among patients with severe infections.

The Journal of antimicrobial chemotherapy·2026
Same journal

Emerging resistance in staphylococci following long-term dalbavancin treatment for prosthetic joint infections.

The Journal of antimicrobial chemotherapy·2026
Same journal

Microbiology testing around the time of antibiotic initiation among residents of long-term care facilities.

The Journal of antimicrobial chemotherapy·2026
Same journal

Insights into the mechanisms underlying cell wall-active agents and gentamicin bactericidal synergism against Enterococcus faecalis.

The Journal of antimicrobial chemotherapy·2026
See all related articles

Understanding bacterial resistance is crucial for patient treatment and selecting effective antibiotics. Mathematical models can predict antibiotic policy outcomes using pooled resistance data.

Area of Science:

  • Microbiology and Infectious Diseases
  • Mathematical Modeling
  • Public Health Surveillance

Background:

  • Bacterial resistance impacts individual patient antimicrobial treatment efficacy.
  • Surveillance data from diagnostic reports guide empirical antibiotic therapy selection.
  • Resistance data offers potential beyond immediate clinical application.

Discussion:

  • Synthesizing diverse resistance data is increasingly necessary.
  • Mathematical models can be developed from this data.
  • These models serve as predictive tools for antibiotic policy.

Key Insights:

  • Individual patient data contributes to broader surveillance efforts.
  • Effective empirical therapy relies on accurate resistance information.

Related Experiment Videos

  • Predictive modeling enhances antibiotic stewardship strategies.

    • Outlook:

    • Future antibiotic policies can be informed by predictive models.
    • Integrating clinical and surveillance data is key.
    • Proactive strategies can mitigate the spread of antimicrobial resistance.